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This book presents the first mathematical formalization of the statistical regularities of non-stochastic randomness and demonstrates how these regularities extend the standard probability-based model of decision making under uncertainty, allowing for the description of uncertain mass events that do not fit standard stochastic models.

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"Decision Systems and Non-stochastic Randomness" presents the first mathematical formalization of the statistical regularities of non-stochastic randomness and demonstrates how these regularities extend the standard probability-based model of decision making under uncertainty, allowing for the description of uncertain mass events that do not fit standard stochastic models. The formalism of statistical regularities developed in this book will have a significant influence on decision theory and information theory as well as numerous other disciplines.

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Decision Systems.- Indifferent Uncertainty.- Nonstochastic Randomness.- General Decision Problems.- Experiment in Decision Problems.- Informativity of Experiment in Bayesian Decision Problems.- Reducibility of Experiments in Multistep Decision Problems.- Concluding Remarks.

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